How to prevent image recognition of my dataset with neural networks and make it hard to train them?
If the model is trained and held constant, then there are so-called adversarial attacks to modify images such that the model classifies them incorrectly (see Attacking Machine Learning
with Adversarial Examples).
However, if you want to make images that are untrainable, you are probably out of luck. Deep neural networks can learn to recognize even random images with random labels (see Understanding deep learning requires rethinking generalization), though if there's no rhyme or reason to the randomness, they won't generalize in meaningful ways.